Course Overview

GCP Engineering and Streaming Architecture

Online, Self-Paced

Course Description

Feature engineering can be an essential tool in applied machine learning when enhancing a dataset. In this course, you will learn about concepts of feature engineering, including areas of streaming architecture and implementations.

Learning Objectives

GCP Feature Engineering

start the course

describe the concepts of feature engineering

recall the benefits of quality features with feature engineering and feature selection

describe the process of input selection in feature engineering

demonstrate feature engineering in use cases

Streaming Architecture

recall the concepts of streaming data and real-time stream processing

describe Dataflow triggers and late data

install Java JDK on Windows 10

demonstrate how to install Apache Maven on Windows 10

install Google Cloud SDK and initialize SDK Shell on Windows 10

demonstrate the process of streaming pipelines using Dataflow SDK 2.x and Java in Cloud SDK Shell

demonstrate the process of streaming pipelines using Dataflow SDK 2.x and Python in Google Cloud Shell

Practice: Feature Engineering and Streaming

describe feature engineering concepts and streaming data architecture

Framework Connections

The materials within this course focus on the Knowledge Skills and Abilities (KSAs) identified within the Specialty Areas listed below. Click to view Specialty Area details within the interactive National Cybersecurity Workforce Framework.